{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 研究假设\n",
    "\n",
    "1. 品牌的营销策略影响公众号的传播效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "数据表 = pd.read_excel(R'data\\编码表 (3).xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import mytools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
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     "text": [
      "相关比率：0.020363008041298314\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'低度相关'"
      ]
     },
     "execution_count": 23,
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   ],
   "source": [
    "a,result = mytools.类别变量与数值变量统计分析(数据表,'推文类型','阅读量')\n",
    "mytools.相关比率强弱判断(a)"
   ]
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   "execution_count": 24,
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       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>           <td>阅读量</td>       <th>  R-squared:         </th> <td>   0.020</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.017</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   6.340</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Thu, 14 Dec 2023</td> <th>  Prob (F-statistic):</th>  <td>0.00188</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>18:02:28</td>     <th>  Log-Likelihood:    </th> <td> -7270.7</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>   613</td>      <th>  AIC:               </th> <td>1.455e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>   610</td>      <th>  BIC:               </th> <td>1.456e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     2</td>      <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>    \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "         <td></td>            <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>       <td> 6.269e+04</td> <td> 1929.183</td> <td>   32.493</td> <td> 0.000</td> <td> 5.89e+04</td> <td> 6.65e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>推文类型[T.信息介绍型推文]</th> <td> 9497.6085</td> <td> 2806.413</td> <td>    3.384</td> <td> 0.001</td> <td> 3986.205</td> <td>  1.5e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>推文类型[T.其他型推文]</th>   <td>-6601.9947</td> <td> 1.01e+04</td> <td>   -0.654</td> <td> 0.514</td> <td>-2.64e+04</td> <td> 1.32e+04</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>5656.590</td> <th>  Durbin-Watson:     </th> <td>   0.147</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>  68.812</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td>-0.362</td>  <th>  Prob(JB):          </th> <td>1.14e-15</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>       <td> 1.526</td>  <th>  Cond. No.          </th> <td>    8.21</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/latex": [
       "\\begin{center}\n",
       "\\begin{tabular}{lclc}\n",
       "\\toprule\n",
       "\\textbf{Dep. Variable:}    &       阅读量        & \\textbf{  R-squared:         } &     0.020   \\\\\n",
       "\\textbf{Model:}            &       OLS        & \\textbf{  Adj. R-squared:    } &     0.017   \\\\\n",
       "\\textbf{Method:}           &  Least Squares   & \\textbf{  F-statistic:       } &     6.340   \\\\\n",
       "\\textbf{Date:}             & Thu, 14 Dec 2023 & \\textbf{  Prob (F-statistic):} &  0.00188    \\\\\n",
       "\\textbf{Time:}             &     18:02:28     & \\textbf{  Log-Likelihood:    } &   -7270.7   \\\\\n",
       "\\textbf{No. Observations:} &         613      & \\textbf{  AIC:               } & 1.455e+04   \\\\\n",
       "\\textbf{Df Residuals:}     &         610      & \\textbf{  BIC:               } & 1.456e+04   \\\\\n",
       "\\textbf{Df Model:}         &           2      & \\textbf{                     } &             \\\\\n",
       "\\textbf{Covariance Type:}  &    nonrobust     & \\textbf{                     } &             \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lcccccc}\n",
       "                         & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
       "\\midrule\n",
       "\\textbf{Intercept}       &    6.269e+04  &     1929.183     &    32.493  &         0.000        &     5.89e+04    &     6.65e+04     \\\\\n",
       "\\textbf{推文类型[T.信息介绍型推文]} &    9497.6085  &     2806.413     &     3.384  &         0.001        &     3986.205    &      1.5e+04     \\\\\n",
       "\\textbf{推文类型[T.其他型推文]}   &   -6601.9947  &     1.01e+04     &    -0.654  &         0.514        &    -2.64e+04    &     1.32e+04     \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "\\begin{tabular}{lclc}\n",
       "\\textbf{Omnibus:}       & 5656.590 & \\textbf{  Durbin-Watson:     } &    0.147  \\\\\n",
       "\\textbf{Prob(Omnibus):} &   0.000  & \\textbf{  Jarque-Bera (JB):  } &   68.812  \\\\\n",
       "\\textbf{Skew:}          &  -0.362  & \\textbf{  Prob(JB):          } & 1.14e-15  \\\\\n",
       "\\textbf{Kurtosis:}      &   1.526  & \\textbf{  Cond. No.          } &     8.21  \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n",
       "%\\caption{OLS Regression Results}\n",
       "\\end{center}\n",
       "\n",
       "Notes: \\newline\n",
       " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                    阅读量   R-squared:                       0.020\n",
       "Model:                            OLS   Adj. R-squared:                  0.017\n",
       "Method:                 Least Squares   F-statistic:                     6.340\n",
       "Date:                Thu, 14 Dec 2023   Prob (F-statistic):            0.00188\n",
       "Time:                        18:02:28   Log-Likelihood:                -7270.7\n",
       "No. Observations:                 613   AIC:                         1.455e+04\n",
       "Df Residuals:                     610   BIC:                         1.456e+04\n",
       "Df Model:                           2                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "===================================================================================\n",
       "                      coef    std err          t      P>|t|      [0.025      0.975]\n",
       "-----------------------------------------------------------------------------------\n",
       "Intercept        6.269e+04   1929.183     32.493      0.000    5.89e+04    6.65e+04\n",
       "推文类型[T.信息介绍型推文]  9497.6085   2806.413      3.384      0.001    3986.205     1.5e+04\n",
       "推文类型[T.其他型推文]   -6601.9947   1.01e+04     -0.654      0.514   -2.64e+04    1.32e+04\n",
       "==============================================================================\n",
       "Omnibus:                     5656.590   Durbin-Watson:                   0.147\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               68.812\n",
       "Skew:                          -0.362   Prob(JB):                     1.14e-15\n",
       "Kurtosis:                       1.526   Cond. No.                         8.21\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
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         "anchor": "x",
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     },
     "metadata": {},
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    {
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     "output_type": "stream",
     "text": [
      "相关比率：0.0024457631055474494\n"
     ]
    }
   ],
   "source": [
    "# 不同交互方式的推文传播效果存在差异\n",
    "\n",
    "eta平方,result = mytools.类别变量与数值变量统计分析(数据表,'交互方式','互动量')"
   ]
  }
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